# LLM-Finetuning

# PEFT Fine-Tuning Project 🚀

Welcome to the PEFT (Pretraining-Evaluation Fine-Tuning) project repository! This project focuses on efficiently fine-tuning large language models using LoRA and Hugging Face's transformers library.

![](https://huggingface.co/datasets/trl-internal-testing/example-images/resolve/main/images/trl_overview.png)

## Fine Tuning Notebook Table 📑

| Notebook Title                                                                                               | Description                                                                                                                                                                                   | Colab Badge                                                                                                                                                                                                                         |
| ------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **1. Efficiently Train Large Language Models with LoRA and Hugging Face**                              | Details and code for efficient training of large language models using LoRA and Hugging Face.                                                                                                 | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/1.Efficiently_train_Large_Language_Models_with_LoRA_and_Hugging_Face.ipynb) |
| **2. Fine-Tune Your Own Llama 2 Model in a Colab Notebook**                                            | Guide to fine-tuning your Llama 2 model using Colab.                                                                                                                                          | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/2.Fine_Tune_Your_Own_Llama_2_Model_in_a_Colab_Notebook.ipynb)               |
| **3. Guanaco Chatbot Demo with LLaMA-7B Model**                                                        | Showcase of a chatbot demo powered by LLaMA-7B model.                                                                                                                                         | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/3.Guanaco%20Chatbot%20Demo%20with%20LLaMA-7B%20Model.ipynb)                 |
| **4. PEFT Finetune-Bloom-560m-tagger**                                                                 | Project details for PEFT Finetune-Bloom-560m-tagger.                                                                                                                                          | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/4.PEFT%20Finetune-Bloom-560m-tagger.ipynb#scrollTo=MDqJWba-tpnv)            |
| **5. Finetune_Meta_OPT-6-1b_Model_bnb_peft**                                                           | Details and guide for finetuning the Meta OPT-6-1b Model using PEFT and Bloom-560m-tagger.                                                                                                    | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/5.Finetune_Meta_OPT-6-1b_Model_bnb_peft.ipynb)                              |
| **6.Finetune Falcon-7b with BNB Self Supervised Training**                                             | Guide for finetuning Falcon-7b using BNB self-supervised training.                                                                                                                            | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/6.Finetune%20Falcon-7b%20with%20BNB%20Self%20Supervised%20Training.ipynb)   |
| **7.FineTune LLaMa2 with QLoRa**                                                                       | Guide to fine-tune the Llama 2 7B pre-trained model using the PEFT library and QLoRa method                                                                                                   | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/7.FineTune_LLAMA2_with_QLORA.ipynb)                                         |
| **8.Stable_Vicuna13B_8bit_in_Colab**                                                                   | Guide of Fine Tuning Vecuna 13B_8bit                                                                                                                                                          | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/8.Stable_Vicuna13B_8bit_in_Colab.ipynb)                                     |
| **9. GPT-Neo-X-20B-bnb2bit_training**                                                                  | Guide How to train the GPT-NeoX-20B model using bfloat16 precision                                                                                                                            | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/9.GPT-neo-x-20B-bnb_4bit_training.ipynb)                                    |
| **10. MPT-Instruct-30B Model Training**                                                                | MPT-Instruct-30B is a large language model from MosaicML that is trained on a dataset of short-form instructions. It can be used to follow instructions, answer questions, and generate text. | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/10.MPT_Instruct_30B.ipynb)                                                  |
| **11.RLHF_Training_for_CustomDataset_for_AnyModel**                                                    | How train a Model with RLHF training on any LLM model with custom dataset                                                                                                                     | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/11_RLHF_Training_for_CustomDataset_for_AnyModel.ipynb)                      |
| **12.Fine_tuning_Microsoft_Phi_1_5b_on_custom_dataset(dialogstudio)**                                  | How train a model with trl SFT Training on Microsoft Phi 1.5 with custom                                                                                                                      | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/12_Fine_tuning_Microsoft_Phi_1_5b_on_custom_dataset(dialogstudio).ipynb)    |
| **13. Finetuning OpenAI GPT3.5 Turbo**                                                                 | How to finetune GPT 3.5 on your own data                                                                                                                                                      | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/13.Fine_tuning_OpenAI_GPT_3_5_turbo.ipynb)                                  |
| **14. Finetuning Mistral-7b FineTuning Model using Autotrain-advanced**                                | How to finetune Mistral-7b using autotrained-advanced                                                                                                                                         | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/14.Finetuning_Mistral_7b_Using_AutoTrain.ipynb)                             |
| **15. RAG LangChain Tutorial**                                                                         | How to Use RAG using LangChain                                                                                                                                                                | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/15.RAG_LangChain.ipynb)                                                     |
| **16. Knowledge Graph LLM with LangChain PDF Question Answering**                                      | How to build knowledge graph with pdf question answering                                                                                                                                      | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/16.Neo4j_and_LangChain_for_Enhanced_Question_Answering.ipynb)               |
| **17. Text to Knolwedge Graph with OpenAI Function with Neo4j and Langchain Agent Question Answering** | How to build knowledge graph from text or Pdf Document with pdf question Answering                                                                                                            | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/17.OpenAI_Constructing_Graph_for_Questio_Answer.ipynb)                      |

## Contributing 🤝

Contributions are welcome! If you'd like to contribute to this project, feel free to open an issue or submit a pull request.

## License 📝

This project is licensed under the [MIT License](LICENSE).

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Created with ❤️ by [Ashish](https://github.com/ashishpatel26/)
